Visualization and Intelligent Systems Laboratory
VISLab

 

 

Contact Information

VISLab
Winston Chung Hall Room 216
University of California, Riverside
900 University Avenue
Riverside, CA 92521-0425


Tel: (951)-827-3954

CRIS
Bourns College of Engineering
UCR
NSF IGERT on Video Bioinformatics

UCR Collaborators:
CSE
ECE
ME
STAT
PSYC
ENTM
BIOL
BPSC
ECON
MATH
BIOENG
MGNT

Other Collaborators:
Keio University

Other Activities:
IEEE Biometrics Workshop 2019
IEEE Biometrics Workshop 2018
Worshop on DVSN 2009
Multibiometrics Book

Webmaster Contact Information:
Alex Shin
wshin@ece.ucr.edu

Last updated: July 1, 2017

 

 

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Spatiotemporal Dynamics of the Growth of Pollen Tubes Using GFP-tagged RIC4 Videos

Summary

  • Currently pollen tube data is analyzed by hand.
  • Develop algorithms for automated analysis of pollen tube growth captured with GFP tagged videos.
  • Verify current understanding of pollen tube dynamics spatially and temporally.
  • Use four videos (600 frames) for quantifying the results.

Introduction


The current model of pollen tube growth. The enzyme, Rho GTPase, activates two downstream pathways: RIC4 and RIC3. RIC4 tagged with GFP relates polar tube growth to ROP1 activity. RIC3 regulates F-actin growth through the calcium gradient.
Significance
  • RIC4 over expression in N. tabacum results in different phenotype.
  • Polar localization of RIC4 to plasma membrane (PM) results in polar tube growth; non-polar, directional tube growth.
Research Performed
  • Analyze GFP tagged RIC4 video.
  • Quantify displacement of PM and frequency of tip localization.

Technical Approach

1. Forward Wavefront Region Growing
  • Address non-polar localization that leads to non-polar growth.
  • Relates a change in angle of the displacement vector to a non-polar localization.
  • Overcomes non-rigid movement issues.
1.1 Modified wavefront growth algorithm
  • Propagate displacement vectors pixel by pixel outward from current points to next frame in video.
  • Smooth vectors to provide better representation of displacement.

Best match points from previous frame are mapped to new growth.
A sample video of the algorithm. Displacement vectors (red arrows) are mapped to the points in the next frame (white border).
2. Analysis of RIC4 Localization
  • Verification of periodicity of RIC4 localization.
  • Algorithm for Oscillation Analysis
    • Histogram analysis to select threshold to report localization of RIC4.
    • Use rotation to register all frames in identical direction.
    • Generate signal for centroid movement corresponding to fluoresce.
    • Compute Fourier transform to characterize frequency domain behavior.

Experimental Results

Laser Microscopy Video
  • Four videos of pollen tube growth with GFP-tagged RIC4.
    • Three videos of 120 frames each, 10 s.
    • One video of 240 frames, 20 s. with over expressed RIC4 stabilized with LatB.
1. Wavefront Results

Frames displaying forward wavefront growing. From left to right: two frames of non-polar growth and one frame of polar growth. Note RIC4 localization to growth area.
2. Signal Generation

Centroid movement accurately reports GFP fluorescence and RIC4 localization. (Lower Right) A signal generated from the sample frames.
3. Oscillation

3.1. Superimposed on Growth Rate

In correlation with previous research[2], tip growth lags behind RIC4 activity, and Rho GTPase activity. Arrows correspond to lagging peaks.
3.2. Periodicity Analysis

Fourier analysis indicates common signal in all data. Signal is low frequency, and is not due to noise.

Conclusions

  • RIC4 localization directs both polar and non-polar pollen tube growth.
  • Localization oscillation exhibits periodic behavior.
  • Experimental results show potential of computer vision with fluorescently tagged videos.
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